1. Field of the Invention
The present invention relates to a digital image coding technique, and in particular to a digital image coding device and method which compresses digital image data inputted from an image input device, a still-image capturing device, and the like.
2. Description of the Related Art
With the widespread use of information processing devices such as personal computers, an increasing number of image scanners or digital cameras have been widely used to input still images into personal computers. Captured still images may be attached to e-mails, presentation documents or Homepages on the Internet. In such a situation that digital imagery is expanding in quality, size and application, there is a growing need for image compression with flexibility and efficiency. The still-image input devices also use an image compression system to store compressed image data.
To efficiently compress a still image with high quality, JPEG (Joint Photographic Experts Group) and then JPEG2000 have been proposed. JPEG2000 is an image coding system employing compression techniques based on wavelet transform technology and has various significant advantages over existing image compression standards. For example, JPEG2000 can provide both lossy and lossless compression and especially allows lossless compression at the same performance level as the original JPEG.
In general, a JPEG2000 coding system is composed of a DC level conversion section, a color transform section, wavelet transform section, quantization section, coefficient modeling section, arithmetic coding section, and code-ordering control section.
However, digital image data inputted from an image capturing device such as an image scanner or digital camera inevitably includes noises which are caused by image sensor, analog circuit, analog-to-digital converter, and the like. Accordingly, when an analog image signal is converted into digital form, several low-order bits of the digital image signal reflect noises and such noise-reflected digital image signal is converted into coefficients by the wavelet transform, resulting in the coefficients to be subject to code modeling having magnitudes influenced by the noises. More specifically, the coefficients obtained by the wavelet transform are divided into a plurality of sub-bitplanes before arithmetic coding. Accordingly, several lower-order sub-bitplanes reflecting the noises are encoded by the arithmetic coder, resulting in an increased amount of code data.